A novel approach towards 2D Facial Aging (FA) techniques using Neural Network (NN) is proposed
in this study. This approach is proposed to automatically predicate the position, number and length of wrinkles
on the forehead area. The method is divided into three main stages; the first stage is the preprocessing stage,
where the forehead area is manually cropped then filtered to gain sharpness. After that, the wrinkles
segmentation process is carried out using row-by-row threshold, morphological erosion and connected
component labeling to accurately extract the wrinkles form the image. Finally, the NN is used to convert the
detected wrinkle lengths from 2D to 3D curvature shape. The proposed method is objectively compared with
other techniques and can accurately predict the position, number and length of the forehead wrinkles in different
ages.

Ayman AbuBaker and Ali Mehdi, 2012. Estimating the Position, Number and Length of Forehead Wrinkles Using Neural Network.
Research Journal of Applied Sciences, Engineering and Technology, 4(15): 2584-2589.